INFORMATION FLOWS IN CAUSAL NETWORKS

We use a notion of causal independence based on intervention, which is a fundamental concept of the theory of causal networks, to define a measure for the strength of a causal effect. We call this measure "information flow" and compare it with known information flow measures such as transfer entropy.

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Year of publication:	2008
Authors:	AY, NIHAT ; POLANI, DANIEL
Published in:	Advances in Complex Systems (ACS). - World Scientific Publishing Co. Pte. Ltd., ISSN 1793-6802. - Vol. 11.2008, 01, p. 17-41
Publisher:	World Scientific Publishing Co. Pte. Ltd.
Subject:	Causality \| information theory \| information flow \| Bayesian networks

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Extent:	application/pdf text/html
Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005080941